
<h1><span class="yiyi-st" id="yiyi-13">numpy.ma.dstack</span></h1>
        <blockquote>
        <p>原文：<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.ma.dstack.html">https://docs.scipy.org/doc/numpy/reference/generated/numpy.ma.dstack.html</a></p>
        <p>译者：<a href="https://github.com/wizardforcel">飞龙</a> <a href="http://usyiyi.cn/">UsyiyiCN</a></p>
        <p>校对：（虚位以待）</p>
        </blockquote>
    
<dl class="data">
<dt id="numpy.ma.dstack"><span class="yiyi-st" id="yiyi-14"> <code class="descclassname">numpy.ma.</code><code class="descname">dstack</code><span class="sig-paren">(</span><em>tup</em><span class="sig-paren">)</span><em class="property"> = &lt;numpy.ma.extras._fromnxfunction instance&gt;</em></span></dt>
<dd><blockquote>
<div><p><span class="yiyi-st" id="yiyi-15">按照深度顺序（沿第三轴）堆叠数组。</span></p>
<p><span class="yiyi-st" id="yiyi-16">获取一个数组序列，并沿着第三个轴将它们堆叠以构成一个数组。</span><span class="yiyi-st" id="yiyi-17">重建数组除以<em class="xref py py-obj">dsplit</em>。</span><span class="yiyi-st" id="yiyi-18">这是将2D数组（图像）堆叠到单个3D数组中进行处理的简单方法。</span></p>
</div></blockquote>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name">
<col class="field-body">
<tbody valign="top">
<tr class="field-odd field"><th class="field-name"><span class="yiyi-st" id="yiyi-19">参数：</span></th><td class="field-body"><p class="first"><span class="yiyi-st" id="yiyi-20"><strong>tup</strong>：数组的序列</span></p>
<blockquote>
<div><p><span class="yiyi-st" id="yiyi-21">数组到堆栈。</span><span class="yiyi-st" id="yiyi-22">除了第三轴之外，它们都必须具有相同的形状。</span></p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name"><span class="yiyi-st" id="yiyi-23">返回：</span></th><td class="field-body"><p class="first"><span class="yiyi-st" id="yiyi-24"><strong>堆叠</strong>：ndarray</span></p>
<blockquote class="last">
<div><p><span class="yiyi-st" id="yiyi-25">通过堆叠给定数组形成的数组。</span></p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title"><span class="yiyi-st" id="yiyi-26">也可以看看</span></p>
<dl class="last docutils">
<dt><span class="yiyi-st" id="yiyi-27"><code class="xref py py-obj docutils literal"><span class="pre">stack</span></code></span></dt>
<dd><span class="yiyi-st" id="yiyi-28">沿着新轴连接数组的序列。</span></dd>
<dt><span class="yiyi-st" id="yiyi-29"><a class="reference internal" href="numpy.ma.vstack.html#numpy.ma.vstack" title="numpy.ma.vstack"><code class="xref py py-obj docutils literal"><span class="pre">vstack</span></code></a></span></dt>
<dd><span class="yiyi-st" id="yiyi-30">沿第一轴堆叠。</span></dd>
<dt><span class="yiyi-st" id="yiyi-31"><a class="reference internal" href="numpy.ma.hstack.html#numpy.ma.hstack" title="numpy.ma.hstack"><code class="xref py py-obj docutils literal"><span class="pre">hstack</span></code></a></span></dt>
<dd><span class="yiyi-st" id="yiyi-32">沿第二轴堆叠。</span></dd>
<dt><span class="yiyi-st" id="yiyi-33"><a class="reference internal" href="numpy.ma.concatenate.html#numpy.ma.concatenate" title="numpy.ma.concatenate"><code class="xref py py-obj docutils literal"><span class="pre">concatenate</span></code></a></span></dt>
<dd><span class="yiyi-st" id="yiyi-34">沿现有轴连接数组序列。</span></dd>
<dt><span class="yiyi-st" id="yiyi-35"><code class="xref py py-obj docutils literal"><span class="pre">dsplit</span></code></span></dt>
<dd><span class="yiyi-st" id="yiyi-36">沿第三轴拆分数组。</span></dd>
</dl>
</div>
<p class="rubric"><span class="yiyi-st" id="yiyi-37">笔记</span></p>
<p><span class="yiyi-st" id="yiyi-38">该函数应用于_data和_mask（如果有）。</span></p>
<p class="rubric"><span class="yiyi-st" id="yiyi-39">例子</span></p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">dstack</span><span class="p">((</span><span class="n">a</span><span class="p">,</span><span class="n">b</span><span class="p">))</span>
<span class="go">array([[[1, 2],</span>
<span class="go">        [2, 3],</span>
<span class="go">        [3, 4]]])</span>
</pre></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">1</span><span class="p">],[</span><span class="mi">2</span><span class="p">],[</span><span class="mi">3</span><span class="p">]])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">2</span><span class="p">],[</span><span class="mi">3</span><span class="p">],[</span><span class="mi">4</span><span class="p">]])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">dstack</span><span class="p">((</span><span class="n">a</span><span class="p">,</span><span class="n">b</span><span class="p">))</span>
<span class="go">array([[[1, 2]],</span>
<span class="go">       [[2, 3]],</span>
<span class="go">       [[3, 4]]])</span>
</pre></div>
</div>
</dd></dl>
